1. Field of the Invention
The present invention relates to image processing, and more specifically, to a method for processing an image using relatively constant CIE XYZ ratios for preserving hue characteristics.
2. Description of the Prior Art
In the past, the unsharp mask (USM) filter has been used to enhance the local contrast (sharpness) of the original image Iorg. The USM filter has been successfully applied in medical imaging and image editing tools. The USM filter operation typically uses a Gaussian low-pass filter to obtain a blurred image Ius, whose blurriness is controlled by a parameter Gaussian radius which indicates Gaussian distribution with radius deviation in Gaussian's probability distribution.
The edge component of the original image is quantified as a (Iorg−Ius) term, which will be multiplied by a β coefficient acting as an amount control parameter. Then, the original image Iorg is added to the enlarged edge component β*(Iorg−Ius) to yield the desired sharper image I″. Many previous patents (such as U.S. Pat. No. 4,317,179 and U.S. Pat. No. 4,315,318) have used a similar concept and formula, which is given in Eqn. 1:I′=Iorg+β*(Iorg−Ius)  (1)
Please refer to FIG. 1. FIG. 1 shows an example of one method for carrying out the operation for obtaining the unsharp mask signal Sus according to the prior art. Referring to FIG. 1, the output of a photodetector 121 which measures the light emitted from the stimulable phosphor upon stimulation is amplified by an amplifier 122 which performs amplification including non-linear correction or band compression such as logarithmic conversion to obtain an original image signal Sorg. The original image signal Sorg is fed to an operation unit 123 for conducting the unsharp masking process on one hand and on the other hand sent to a low-pass filter 124 to obtain the unsharp mask signal Sus. In the low-pass filter 124, the analog value of Sorg is filtered with only its super-low frequency component being transmitted therethrough and then converted to a digital signal Si by an A/D converter 125. The converted digital signal is used for calculating an arithmetic mean value
  Sus  =            ∑                            ⁢                  ⁢    aiSi  by a digital calculating circuit 126. The obtained value is fed to the operation unit 123 as the unsharp mask signal Sus. In this formula, ai is a weighting coefficient for the signal Si coming from the A/D converter 125. In case of a simple arithmetic mean, ai is made to be equal to 1/N, N being the number of the scanning lines counted in the sub-scanning direction over a range to be covered by an unsharp mask.
As shown in FIG. 1, the original image signal Sorg is fed to the operation unit 123 in the form of an analog signal. Since this signal Sorg has been obtained before the unsharp mask signal Sus is fed to the unit 123, it is necessary to delay the input of the original image signal Sorg so that both the signals Sorg and Sus are simultaneously fed to the unit 123. Alternatively, the original image signal Sorg may be stored in a memory after being converted to a digital value and read out from the memory when it is used together with the unsharp mask signal Sus. In any way, it is necessary to delay the input of the original image signal Sorg into the unit 123 by the time required for the unsharp mask signal Sus to be calculated through the low-pass filter 124, the A/D converter 125 and the circuit 126, so that the signals Sorg and Sus are fed to the operation unit 123 simultaneously.
Another patent, U.S. Pat. No. 5,937,111 uses a similar framework as above and includes extending the estimation of the suitable β coefficient through an image morphology operation. Please refer to FIG. 2. FIG. 2 is a block diagram showing an image processing apparatus according to the prior art. The image processing apparatus illustrated in FIG. 2 carries out image processing on an image signal, which represents an X-ray image, and selectively emphasizes a small calcified pattern, which has a predetermined contour and has an image density value smaller than the image density values of the surrounding image portions.
The image processing apparatus comprises a low pass filter 11 for obtaining an unsharp mask signal Sus, which corresponds to super-low frequency, from an original image signal Sorg, which is an image density signal (a high image density-high signal level type of image signal) representing an image. The image processing apparatus also comprises a subtracter 17 for subtracting the unsharp mask signal Sus from the original image signal Sorg and thereby extracting comparatively high frequency components (Sorg−Sus). The image processing apparatus further comprises a calcified pattern-dependent emphasis coefficient calculating means 20 for extracting a calcified pattern signal, which represents a calcified pattern, from the original image signal Sorg and calculating a first emphasis coefficient βcalc, which is dependent upon the calcified pattern signal. The image processing apparatus still further comprises an edge signal-dependent emphasis coefficient calculating means 30 for extracting an edge signal, which represents an image edge portion, from the original image signal Sorg and calculating a second emphasis coefficient βedge, which is dependent upon the edge signal. The image processing apparatus also comprises a multiplier 41 for multiplying the first emphasis coefficient βcalc and the second emphasis coefficient βedge by each other and thereby calculating a single emphasis coefficient β. The image processing apparatus further comprises a multiplier 42 and an adder 43, which carry out the signal processing with the formula Sproc=Sorg+β*(Sorg−Sus) by using the original image signal Sorg, the high frequency components (Sorg−Sus), and the emphasis coefficient β and thereby obtain a processed image signal Sproc.
In U.S. Pat. No. 6,072,913, extending one specific radius Gaussian filter to set with N various radiuses is taught. The various radius set is used to construct the frequency banded image. Then, the difference of the desired frequency response and the current frequency is calculated to provide good control to the USM band filter.
These methods typically apply the USM filter on device or detector″s signal. Unfortunately, the prior art techniques all have at least two common drawbacks. First of all, the prior art methods generate complementary hue surrounding object hue color when applying USM filters. This does not offer good color reproduction. Secondly, the prior art methods involve complex computation or unnecessarily repeated computation on device signal channels. For instance, a separate pass of the algorithm is used for each of the colors red, green, and blue (RGB) instead of processing the image in one pass. Similarly, if the colors cyan, magenta, yellow, and black are used, four passes will be required.